Modern medical imaging methods such as, for example, X-ray computed tomography, can be used to obtain tomographic image data of an examined measurement object, for example a patient. X-ray computed tomography is a specific X-ray recording method with the aid of which it is possible to obtain transverse sectional images, that is to say images of body slices that are aligned substantially perpendicular to the body axis. The tissue-specific physical quantity represented in the image is the distribution of the attenuation value of X-radiation μ(x, y) in the sectional plane. In addition to these transverse sectional images, it is also possible to obtain volume images of the acquired object area that represent the three-dimensional distribution of X-ray attenuation values μ(x, y, z). Each volume element, also termed voxel, of the acquired object area is in this case assigned an X-ray attenuation value.
CT images can be generated both with the aid of a conventional computer tomograph having a scanning system that can revolve endlessly, and by way of a C-bow unit. The term CT is used below for both types of imaging units.
The CT image data are calculated with the aid of a reconstruction algorithm from the raw data supplied by the CT unit, which algorithm includes convolution with the aid of a specific convolution core (kernel). Owing to the mathematical configuration of the convolution core, it is possible for the image quality to be influenced specifically when reconstructing a CT image from the raw data. For example, a suitable convolution core can be used to emphasize high frequencies in order to raise the spatial resolution in the image or—with the aid of a convolution core of an appropriately different type—to lower it, in order to reduce the image noise. Thus, during image reconstruction in computed tomography it is possible to use the selection of the convolution core to influence the image characteristic that is characterized by image sharpness/image noise and image contrast.
It is currently necessary to calculate CT images from manufacturer- and product-specific raw data on high power image reconstruction computers developed specifically therefore. In this case, the raw data are stored in a manufacturer-specific format and include no pixel or voxel data. They can therefore not be brought directly to the display, but serve exclusively to reconstruct images or image series.
However, users frequently require different views of the acquired object area with different image parameters. To date, this has required using the raw data to calculate any desired number of series of sectional images by reconstructing the raw data with the aid of different settings, for example with the aid of a different core, different slice thickness, different increment, different FoV (Field of View) or different orientation. Since these parameters and the associated reconstruction algorithms are, however, closely linked to the CT unit that was used to acquire the object area, they are also different for each manufacturer and each type of unit. The desired sectional images can therefore be reconstructed without a problem from the raw data only on the CT system on which they are also acquired.
These series of sectional images form the basis for postprocessing, archiving, transfer to other image processing or imaging units and, finally, diagnosis. The so-called DICOM (Digital Imaging and Communications in Medicine) standard is used for the transfer. Images and data from different imaging and image processing units can be exchanged among one another with the aid of this standard. However, in addition to the storage requirement for the raw data, the provision of different image series also necessitates the storage requirement for the image series, and this can certainly amount to several gigabytes.
Consequently, transferring the image series and loading them into CT applications for the purpose of postprocessing are also very time consuming and disadvantageously impair the clinical workflow. The reconstruction of different image series from the raw data likewise requires a substantial time outlay. Keeping the raw data to hand on the CT system for the purpose of later reconstruction requires a great deal of storage and is therefore very restricted in time for reasons of cost. As a rule, the raw data can currently be kept to hand only for a few days. The raw data can also be archived on optical storage media, for example, in order to lengthen the time at which they can be kept to hand. However, the archiving operation and the later importing of the raw data are likewise time consuming, and are therefore scarcely carried out in practice.
For the purpose of reproducibly generating views of CT image data, the DICOM standard discloses the so-called 2D presentation states in which the value range of the CT values that is to be displayed, the so-called window, the image segment in pixel data, as well as a digital zoom onto the pixel data are stored. The so-called gray scale, color and blending presentation states enable the filing of color and/or gray scale coding tables and of rotation and transformation matrices for a linear registration with transformation for two image series (PET-CT, SPECT-CT). An organ-referred view of a volume or volume segment (3D object) with a variable image impression, that is to say different image sharpness/image noise or different image contrast, is therefore impossible.